Pedestrian dynamics model for high densities

This paper presents a novel Cellular Automata (CA) model for crowd simulations, aimed at understanding pedestrian dynamics in high-density environments. The model incorporates static and dynamic floor fields, multi-cell representations of pedestrians, and a mechanism for simulating blockades, where individuals may be pushed towards walls. Inspired by Burstedde’s work, our model enhances realism and accuracy in crowd behavior simulations. It was validated against real-world experiments involving 68 students, focusing on pedestrian density, cumulative percent flow through bottlenecks, and Voronoi density. Comparisons with the Burstedde et al. model show that our approach provides more accurate simulations for scenarios involving highly motivated pedestrians navigating through bottlenecks. These findings contribute to the development of more effective crowd management strategies and advanced simulation techniques. • High Accuracy in Simulating High-Density Crowds Through Bottlenecks: The model outperforms Burstedde’s in terms of transition times, density, and flow. • Improved Bottleneck Simulation: Effectively handles multi-cell pedestrians and pressure blockages. • Realistic Density and Flow: The model closely matches experimental data, achieving higher correlation. • Enhanced Versatility: Supports various special movement scenarios, improving adaptability to a wide range of situations.